Systems and methods for drug therapy enhancement using expected pharmacodynamic models

• US 20060089592A1
• Filed: 10/21/2004
• Published: 04/27/2006
• Est. Priority Date: 10/21/2004
• Status: Active Grant

• Current Assignee: Cardiac Pacemakers Incorporated (Boston Scientific Corporation)
• Original Assignee: Cardiac Pacemakers Incorporated (Boston Scientific Corporation)
• Inventors: Kadhiresan, Veerichetty, Brockway, Marina, Carlson, Gerrard C.
• Granted Patent: US 8,150,509 B2
• Time in Patent Office: Days
• US Class Current: 604/65
• CPC Class Codes: A61M 2005/14208 with a programmable infusion control system, characterised by the infusion program
• CPC Class Codes: A61M 2205/3523 using telemetric means
• CPC Class Codes: A61M 2205/3561 local, e.g. within room or hospital
• CPC Class Codes: A61M 2230/04 Heartbeat characteristics, e.g. ECG, blood pressure modulation
• CPC Class Codes: A61M 2230/08 Other bio-electrical signals
• CPC Class Codes: A61M 2230/30 Blood pressure A61M2230/04 takes precedence
• CPC Class Codes: A61M 2230/50 Temperature
• CPC Class Codes: A61M 2230/63 Motion, e.g. physical activity
• CPC Class Codes: A61M 5/142 Pressure infusion, e.g. using pumps
• CPC Class Codes: A61M 5/14276 specially adapted for implantation
• CPC Class Codes: A61M 5/1723 using feedback of body parameters, e.g. blood-sugar, pressure measurement of body parameters A61B5/00
• CPC Class Codes: G16H 20/13 delivered from dispensers
• CPC Class Codes: G16H 20/17 delivered via infusion or injection
• CPC Class Codes: G16H 50/50 for simulation or modelling of medical disorders
• CPC Class Codes: G16H 70/40 relating to drugs, e.g. their side effects or intended usage
• CPC Class Codes: Y10S 128/923 by comparison of patient data to other data

Abstract

A system or method including a device configured to measure at least one pharmacological effect of a drug on a patient. The measured pharmacological effect is compared to an expected pharmacodynamic model. The system can allow for real-time monitoring of positive and side-effects of drugs as well as drug resistance to optimize individual therapy. The system can also enable patient compliance monitoring.

Claims

1. An advanced patient management system, comprising:

a device configured to measure data associated with at least one pharmacological effect of a drug on a patient;

a repeater unit in communication with the device and a network; and

a host in communication with the device through the network and the repeater, the host including a database module and an analysis module;

wherein the database module is configured to store the data from the device, and wherein the analysis module is configured to compare the data to an expected pharmacodynamic model.

2. The system of claim 1, further comprising a drug dispenser in communication with the repeater unit, the drug dispenser dispensing the drug and communicating a time that the drug is dispensed to the host.

3. The system of claim 2, wherein the drug dispenser is a drug pump.

4. The system of claim 3, wherein the drug pump dispenses the drug based on the comparison of the data to the expected pharmacodynamic model.

5. The system of claim 1, wherein the analysis module determines drug therapy regimen compliance based on the comparison of the data to the expected pharmacodynamic model.

6. The system of claim 5, wherein the analysis module generates a compliance report based on the drug therapy regimen compliance.

7. The system of claim 1, wherein the analysis module identifies an unexpected effect based on the comparison of the data to the expected pharmacodynamic model.

8. The system of claim 7, wherein the analysis module generates a side-effect report based on the unexpected effect.

9. The system of claim 7, wherein the analysis module generates a drug resistance report based on the unexpected effect.

10. The system of claim 7, wherein the analysis module generates an alarm based on the unexpected effect.

11. The system of claim 10, wherein the host communicates the alarm to the patient.

12. The system of claim 1, wherein the analysis module is configured to suggest modification of the drug therapy regimen based on the comparison of the data to the expected pharmacodynamic model.

13. The system of claim 1, wherein the device is an implanted device.

14. The system of claim 1, wherein the device is a non-implanted device.

15. The system of claim 1, wherein the pharmacological effect is at least one selected from the group consisting of activity level, weight, brachial and intracardiac or systemic blood pressure, heart rate, thoracic impedance, heart sounds, and heart rate variability.

16. The system of claim 1, wherein the expected pharmacodynamic model is selected based on at least one characteristic of the patient.

17. The system of claim 16, wherein the characteristic is selected from the group consisting of medical history, age, race, national origin, and gender.

18. The system of claim 1, wherein the analysis module creates the expected pharmacodynamic model for the patient based on the data measured by the device.

19. The system of claim 1, wherein the analysis automatically module selects the expected pharmacodynamic model for the patient based on the data measured by the device.

20. A method of enhancing drug therapy in an advanced patient management system, comprising:

measuring data associated with at least one pharmacological effect of a drug on a patient;

communicating the data to a host; and

comparing the data to an expected pharmacodynamic model.

21. The method of claim 20, further comprising:

dispensing the drug; and

communicating a time that the drug is dispensed to the host.

22. The method of claim 20, wherein the comparing step further comprises determining drug therapy regimen compliance based on comparison of the data to the expected pharmacodynamic model.

23. The method of claim 22, further comprising generating a compliance report based on the drug therapy regimen compliance.

24. The method of claim 20, wherein the comparing step further comprises identifying an unexpected effect based on comparison of the data to the expected pharmacodynamic model.

25. The method of claim 24, further comprising generating a side-effect report based on the unexpected effect.

26. The method of claim 24, further comprising generating a drug resistance report based on the unexpected effect.

27. The method of claim 24, further comprising generating an alarm based on the unexpected effect.

28. The method of claim 27, further comprising forwarding the alarm to the patient.

29. The method of claim 20, further comprising suggesting modification of the drug therapy regimen automatically based on comparison of the data to the expected pharmacodynamic model.

30. The method of claim 20, wherein the step of measuring further comprises using a non-implanted device to measure the data associated with the pharmacological effect of the drug on the patient.

31. The method of claim 20, further comprising selecting the expected pharmacodynamic model based on at least one characteristic of the patient.

32. The method of claim 20, further comprising creating the expected pharmacodynamic model for the patient based on the data.